The FOVEAL project aims at developing a novel theoretical framework for understanding the muscle force production capacity as a function of time and contraction velocity during animal locomotion. This project rely on a multidisciplinary research team including specialists in applied mathematics, muscle biology, integrative physiology, biomechanics and ecology. We will first propose a mathematical model that describes the force-velocity-endurance capacity. This relation will make possible to understand the animal locomotion capacities when the mechanical constraints are variable (e.g. in mountains). As this relation seems valid from the organ (muscle) to the function (locomotion) and across species, the proposed approach originality is to take advantage of different experimental models (scales and species) to address the different research questions. Thus, in situ muscle mice model will provide insight at the muscle level thanks to functional, histological and biochemical analysis; running human model is the cornerstone as it allows to test our hypothesis and validate the methodological approach in both laboratory-controlled conditions (running treadmill) and natural environment (trail running). Integrative exercise physiology approach will also be possible in humans to understand the mechanisms involved in the individual force-velocity-endurance characteristics Finally, wild chamois model will permit to develop a non-invasive evaluation methodology of wild animals in their natural environment presenting variable mechanical conditions. This will provide insights in the relationships between the muscle organ and the locomotor function, and between the capacities of individuals and the requirements of the physical activity being health/performance (human) or survival (animals).

Marine megafauna includes marine mammals, sea turtles, sharks and rays that are increasingly threatened worldwide. These species occur at low densities over vast areas so an efficient and large-scale monitoring method is urgently needed to identify and protect their critical habitats. Drones are emerging low-cost and low-carbon technologies for monitoring megafauna from the air. However, existing drone surveys fail to achieve both large spatial coverage and high image resolution. The higher the drone altitude, the larger spatial coverage but at the expense of image resolution. Yet, high image resolution is key to derive accurate species identifications and individual body measurements. To break this compromise between spatial coverage and image resolution, the overall objective of SMART-WING is to design an adaptive survey methodology based on an intelligent wing able to switch between high and low altitude modes. We will embed an artificial intelligence (AI) detection model in a vertical take-off and landing (VTOL) wing characterized by a flexible long-range flight. The wing will be pre-programmed in high-altitude mode (160 m for ~2 cm / pixel ground resolution) for large-scale survey coverage. In the event of megafauna detection, it will descend to lower altitude (40 m) and dynamically track the animal, transitioning from horizontal survey to vertical hovering to acquire high-resolution images (~0.5 cm / pixel), so representing a 4-time gain in ground resolution. The wing will then resume its initial high-altitude survey. We hypothesise that this novel method will provide an increased image resolution without compromising spatial coverage. We will implement SMART-WING in the vast lagoon of Mayotte hosting exceptional but poorly known populations of marine mammals, sea turtles, sharks and rays. SMART-WING will provide novel ecological information on megafauna populations at low financial and carbon costs toward the identification of key areas for their protection. The project has 3 scientific objectives: 1) Develop a smart wing prototype. We will develop an affordable, long-endurance, eco-responsible and easy-to-operate VTOL wing able to fly both horizontally and vertically. The wing will be equipped with a mini-computer embedding a lightweight AI model to detect megafauna species in real time. We will implement a re-routing algorithm on the wing’s autopilot in order to adapt the trajectory to real-time detections. The wing prototype will be tested in coastal habitats of the Mediterranean Sea and then in Mayotte to gradually improve its operational performance. 2) Monitor species-specific abundances and body characteristics. We will deploy the wing to monitor megafauna across thousands of hectares in Mayotte’s coastal habitats during 2 seasons and 2 successive years. We will analyse the collected images with a full-size AI model, quantifying performance gain when switching from the high-altitude and to the low-altitude flight mode. We will then apply this AI model to high-resolution images to estimate species-specific abundances as well as individual sizes and body conditions. 3) Simulate marine protected area (MPAs) scenarios to safeguard megafauna. We will build statistical models to relate species-specific abundances and relevant environmental predictors in order to provide abundance predictions in unsurveyed areas of Mayotte. We will then use systematic conservation planning algorithms to derive scenarios of strict MPA establishment for safeguarding megafauna while accounting for the loss of fishery catches. SMART-WING will pave the way toward the development of a new generation of drones able to dynamically adjust their trajectory in real time for the optimised survey of rare and vulnerable species. It will foster cross-domain interactions between scientists in aerial robotics (I3S and ISEN), artificial intelligence (LIRMM), marine ecology (CUFR, MARBEC) and environmental management (OFB-PMM).

Abalone is a low trophic herbivorous gastropod feeding on seaweed. It has been consumed for centuries as a traditional dish in many parts of the world. This species is fished professionally and recreationally in France. However, wild abalone stocks have declined sharply in France due to massive mortalities caused by a pathogenic bacterium, Vibrio harveyi, with a mortality up to 80% in Brittany and Normandy at the end of the nineties when sea-water temperature reached over 18°C in summer. Impacted populations have not recovered. Ranching, which is an extensive rearing method consisting of implanting juveniles in the natural environment, stock enhancement, which consists of increasing or maintaining fisheries, and restocking, which consists of implanting juveniles to re-establish disappeared stocks, could be opportunities to develop new opportunities for the preservation of this emblematic species. The juveniles are reared in nurseries and produced from wild or domesticated broodstock depending of the objective. The implantation of abalone for stock enhancement has been carried out for many years in countries such as Japan, Mexico and South Africa. However, the technique for implanting abalone in the natural environment is not currently mastered in France, nor is the equipment associated with these implantations. Moreover, certain technical obstacles have still to be overcome. Technical obstacles remain, with a mortality of 90% in average, observed mainly just after seeding. ORMER, an experimental development project, aims at developing innovative tools to enable the establishment of sustainable abalone restocking with a transdisciplinary approach. The following hypothesis will be tested: 1) Initial mortality can be minimised by conditioning hatchery juveniles to predators and using optimised seeding techniques 2) improved knowledge of the ecosystem carrying capacity of seeding sites considering juvenile density and size can improve survival in ranching and stock enhancement programmes at an operational scale 3) Better understanding of the wild populations genetic structure, the assessment of health status and immune priming of juveniles prior to seeding can mitigate the risk associated with reseeding operations 4) Assessment of social acceptability, as well as long-term economic viability are necessary keystones to ensure sustainable development of restoration, stock-enhancement or ranching programmes. Partners from the socio-professional sector (including an aquaculture company and the Iroise Marine Natural Park) as well as researchers from different disciplines (ethology, ecology, genetics, pathology, economics and sociology) will work together to develop sustainable stocking programmes to provide the necessary keys to decision-makers (business leaders, fishers, national parks) on social, economic and technical aspects. The expectations of each stakeholder (professional and recreational fishers, aquaculture, ecological rehabilitation) will be included into the project.

EO4wildlife main objective is to bring large number of multidisciplinary scientists such as biologists, ecologists and ornithologists around the world to collaborate closely together while using European Sentinel Copernicus Earth Observation more heavily and efficiently. In order to reach such important objective, an open service platform and interoperable toolbox will be designed and developed. It will offer high level services that can be accessed by scientists to perform their respective research. The platform front end will be easy-to-use, access and offer dedicated services that will enable them process their geospatial environmental stimulations using Sentinel Earth Observation data that are intelligently combined with other observation sources. Specifically, the EO4wildlife platform will enable the integration of Sentinel data, ARGOS archive databases and real time thematic databank portals, including Wildlifetracking.org, Seabirdtracking.org, and other Earth Observation and MetOcean databases; locally or remotely, and simultaneously. EO4wildlife research specialises in the intelligent management big data, processing, advanced analytics and a Knowledge Base for wildlife migratory behaviour and trends forecast. The research will lead to the development of web-enabled open services using OGC standards for sensor observation and measurements and data processing of heterogeneous geospatial observation data and uncertainties. EO4wildlife will design, implement and validate various scenarios based on real operational use case requirements in the field of wildlife migrations, habitats and behaviour. These include: (1) Management tools for regulatory authorities to achieve real-time advanced decision-making on the protection of protect seabird species; (2) Enhancing scientific knowledge of pelagic fish migrations routes, reproduction and feeding behaviours for better species management; and (3) Setting up tools to assist marine protected areas and management.